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| author | Rémi Flamary <remi.flamary@gmail.com> | 2019-11-18 11:13:03 +0100 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2019-11-18 11:13:03 +0100 |
| commit | bbd8f2046ec42751eba8e5356366aded74a2930d (patch) | |
| tree | 6e8b8ceb9bfc59257360ef2d2d54417a8041a30e /ot/optim.py | |
| parent | 3635fc46d6fc55e6fa30b33ad07fe092dfd23241 (diff) | |
| parent | 0280a3441b09c781035cda3b74213ec92026ff9e (diff) | |
Merge pull request #108 from kilianFatras/master
[MRG] Fix log and nbiter bug in gromov_wasserstein and gromov_wasserstein2
Diffstat (limited to 'ot/optim.py')
| -rw-r--r-- | ot/optim.py | 6 |
1 files changed, 4 insertions, 2 deletions
diff --git a/ot/optim.py b/ot/optim.py index 0abd9e9..4012e0d 100644 --- a/ot/optim.py +++ b/ot/optim.py @@ -134,7 +134,7 @@ def solve_linesearch(cost, G, deltaG, Mi, f_val, return alpha, fc, f_val -def cg(a, b, M, reg, f, df, G0=None, numItermax=200, +def cg(a, b, M, reg, f, df, G0=None, numItermax=200, numItermaxEmd=100000, stopThr=1e-9, stopThr2=1e-9, verbose=False, log=False, **kwargs): """ Solve the general regularized OT problem with conditional gradient @@ -172,6 +172,8 @@ def cg(a, b, M, reg, f, df, G0=None, numItermax=200, initial guess (default is indep joint density) numItermax : int, optional Max number of iterations + numItermaxEmd : int, optional + Max number of iterations for emd stopThr : float, optional Stop threshol on the relative variation (>0) stopThr2 : float, optional @@ -238,7 +240,7 @@ def cg(a, b, M, reg, f, df, G0=None, numItermax=200, Mi += Mi.min() # solve linear program - Gc = emd(a, b, Mi) + Gc = emd(a, b, Mi, numItermax=numItermaxEmd) deltaG = Gc - G |